Asymptotic statistical properties of AR spectral estimators for processes with mixed spectra

Author

Lau, Soon-Sen ; Sherman, Peter J. ; White, Langford B.

Author_Institution

Qualcomm Inc., San Diego, CA, USA

Volume

48

Issue

4

fYear

2002

fDate

4/1/2002 12:00:00 AM

Firstpage

909

Lastpage

917

Abstract

The influence of a point spectrum on large sample statistics of the autoregressive (AR) spectral estimator is addressed. In particular, the asymptotic distributions of the AR coefficients, the innovations variance, and the spectral density estimator of a finite-order AR(p) model to a mixed spectrum process are presented. Various asymptotic results regarding AR modeling of a regular process with a continuous spectrum are arrived at as special cases of the results for the mixed spectrum setting. Finally, numerical simulations are performed to verify the analytical results

Keywords

autoregressive processes; parameter estimation; spectral analysis; statistical analysis; AR coefficients; AR modeling; AR spectral estimators; asymptotic statistical properties; autoregressive spectral estimator; continuous spectrum; finite-order model; innovations variance; large sample statistics; mixed spectra processes; mixed spectrum process; numerical simulations; spectral density estimator; Colored noise; Least squares approximation; Linear regression; Numerical simulation; Performance analysis; Predictive models; Spectral analysis; Statistical distributions; Stochastic processes; Technological innovation;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/18.992779

Filename

992779